Bibliographic record
Abstract
Abstract A trade-off between seed mass (SM) and seed output (SO) defines a central axis of ecological variation among plants, with implications for understanding both plant trait evolution and plant responses to environmental change. While an observed negative SM-SO relationship is hypothesized to reflect universal constraints on resource allocation in all plants, domestication has likely fundamentally altered this relationship. Using a dataset of SM and SO for 41 of the world most widespread crops and 1,190 wild plant species, coupled with observational data on these traits in soy ( Glycine max ) and maize ( Zea mays ), I show that domestication has systematically rewired SM-SO relationships in crops. Compared to wild plants, virtually all crops express a higher SM for a given SO; this domestication signature is especially prominent in seed crops, and also influences the phylogenetic signal in SM and SO. In maize these traits have become positively related likely due to simultaneous selection for greater SM and SO, while in soy these traits have become decoupled likely due to primary selection for SM only. Evolved relationships between SM and SO in plants have been disrupted by both conscious and unconscious artificial selection, which represents a key aspect of how the functional biology of crops differ fundamentally from wild plants along “universal” plant trait spectra.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".